University of Canterbury: Autonomous 3D crop scanning for pre-harvest grading, seeking partners and collaborators

Opportunity for

• Farm vehicle and robotics companies building autonomous ground vehicles for orchards and vineyards, looking to integrate a 3D scanning layer
• Sensor, camera and 3D scanning manufacturers interested in co-developing a productised version of the system
• Investors in early-stage agritech, deep tech or hardware-enabled SaaS, who understand the specialty crop value chain, interested in early conversations.

Opportunity description

Industry challenge:

Sampling a farm block periodically takes time and inherently costs more the more sampling you want to do. Despite this, sampling is hugely valuable for getting a better idea of the current state of your plants in terms of yield, vigour, hydration, disease and more. 

Currently, standard practice for obtaining crop estimates involves sampling just 0.1 to 2% of the crop. Depending on the method of sampling, error rates are often between 15 and 25%. This error gets amplified significantly when extrapolating over a whole block. Even modern camera-based systems suffer from a similar range of inaccuracy, as they rely on a calibration stage completed by a farm worker. 

Fruit graders and packhouses are consistently disappointed in the accuracy they are getting from the field and often receive yield estimates that cause a large over or under supply of labour, packaging, production line resources and fruit sales.

Current opportunity:

Holocrop's autonomous 3D sampling system is state-of-the-art and unlocks a new field, pre-harvest grading, allowing fruit producers to sell their fruit with confidence days before it reaches the packhouse. With early commercial trials underway in New Zealand, validation work being finalised in the US, and as the team now looks to extend trials into Australia, they are interested in connecting with strategic partners and integrators who can help accelerate their validation and growth.

Of particular interest are autonomous ground vehicle and robotics companies who see value in integrating Holocrop's 3D scanning and crop perception layer into their existing platforms, as well as sensor, camera and 3D scanning technology providers open to collaborating on a productised version of the system. 

While not currently raising, Holocrop is prepared to start early conversations with investors ahead of a formal raise next year, particularly those with experience in agritech, deep tech or hardware-enabled SaaS and an understanding of the specialty crop value chain.

Opportunity background:

Holocrop is a spin-out from the University of Canterbury in New Zealand, built on research from a multi-year, government-funded MBIE Endeavour programme running through to 2028. The founding team are research engineers with prior industry experience. Holocrop's 3D scanning rovers are already deployed with research partners and the team has active conversations with vehicle manufacturers. The system has been validated across apples, cherries and grapes, with commercial contracts underway in New Zealand and validation work being finalised with Washington State University.

Potential other applications:

Holocrop has strong demand from groups looking to improve their R&D outcomes using its 3D optical phenotyping capabilities. The system's ability to capture the full 3D structure of crop plants makes it highly relevant for research applications, including plant breeding trials, chemical efficacy studies and agronomic assessments where precise, repeatable measurements are critical.